Search Results - (( knowledge solution based algorithm ) OR ( a simulation optimization algorithm ))

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  1. 1

    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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    Thesis
  2. 2

    Pressure vessel design simulation: Implementing of multi-swarm particle swarm optimization by Salih, Sinan Q., Alsewari, Abdulrahman A., Yaseen, Zeher M.

    Published 2019
    “…The new era knowledge of optimization algorithm is massively boosted recently. …”
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    Conference or Workshop Item
  3. 3

    The compact genetic algorithm for likelihood estimator of first order moving average model by Al-Dabbagh, R.D., Baba, M.S., Mekhilef, Saad, Kinsheel, A.

    Published 2012
    “…Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. …”
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  4. 4

    Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization by Kamal Z., Zamli

    Published 2018
    “…Many meta-heuristic algorithms have been developed to date (e.g. Simulated Annealing (SA), Particle Swarm Optimization (PSO), Teaching Learning based Optimization (TLBO), Grey Wolf Optimizer(GWO) to name a few). …”
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  5. 5

    An Assembly Sequence Planning Approach with a Multi-State Particle Swarm Optimization by Ismail, Ibrahim, Zuwairie, Ibrahim, Hamzah, Ahmad, Zulkifli, Md. Yusof

    Published 2016
    “…In this paper, an approach based on a new variant of Particle Swarm Optimization Algorithm (PSO) called the multi-state of Particle Swarm Optimization (MSPSO) is used to solve the assembly sequence planning problem. …”
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    Book Chapter
  6. 6

    Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems by Franco, Daniel Jose Da Graca Peceguina

    Published 2021
    “…Experimental design and simulations are carried out through a quantitative approach, where the proposed solutions perform the anonymization of Modbus/TCP packet fields to achieve acceptable privacy levels for data sets publication and proposes a state-based IDS tailored to Modbus/TCP networks in WDS, taking advantage of a knowledge database and state-based rules’ language to control on systems states and constant specification changes. …”
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    Thesis
  7. 7

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. …”
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    Thesis
  8. 8

    Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller by Zaridah, Mat Zain

    Published 2010
    “…This algorithm encode a potential solution to a specific problem on a simple chromosome like data structure and apply recombination operators to this structure to preserve critical information. …”
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    Thesis
  9. 9

    An Experimental Study of Hyper-heuristic Selection and Acceptance Mechanism for Combinatorial T-Way Test Suite Generation by Kamal Z., Zamli, Fakhrud, Din, Kendall, Graham, Ahmed, Bestoun S.

    Published 2017
    “…Recently, many meta-heuristic algorithms have been proposed to serve as the basis of a t-way test generation strategy (where t indicates the interaction strength) including Genetic Algorithms (GA), Ant Colony Optimization (ACO), Simulated Annealing (SA), Cuckoo Search (CS), Particle Swarm Optimization (PSO), and Harmony Search (HS). …”
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    Article
  10. 10

    A new modern scheme for solving fractal–fractional differential equations based on deep feedforward neural network with multiple hidden layer by Admon, Mohd Rashid, Senu, Norazak, Ahmadian, Ali, Majid, Zanariah Abdul, Salahshour, Soheil

    Published 2024
    “…Thus, this research aims to extend the application of ANN to solve FFDE with power law kernel in Caputo sense (FFDEPC) by develop a vectorized algorithm based on deep feedforward neural network that consists of multiple hidden layer (DFNN-2H) with Adam optimization. …”
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    Article
  11. 11

    Development of optimized maintenance scheduling model for coal-fired power plant boiler by Noor Fazreen Binti Ahmad Fuzi, Ms.

    Published 2023
    “…Literature revealed that mathematical methods and metaheuristic algorithms are common approaches in solving combinatorial optimization problems with a large search space in a reasonable computational run time. …”
    text::Thesis
  12. 12

    SDN-based VANET routing: A comprehensive survey on architectures, protocols, analysis, and future challenges by Hussein, Nehad Hameed, Koh, Siaw Paw, Yaw, Chong Tak, Tiong, Sieh Kiong, Benedict, F., Yusaf, Talal, K., Kadirgama, Tan, Chung Hong

    Published 2024
    “…In addition, a complete comparative analysis will be achieved to analyze the protocols regarding performance, optimization, and simulation results. …”
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    Article
  13. 13

    SDN-Based VANET Routing: A Comprehensive Survey on Architectures, Protocols, Analysis, and Future Challenges by Hussein N.H., Koh S.P., Yaw C.T., Tiong S.K., Benedict F., Yusaf T., Kadirgama K., Hong T.C.

    Published 2025
    “…In addition, a complete comparative analysis will be achieved to analyze the protocols regarding performance, optimization, and simulation results. …”
    Article
  14. 14

    Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm by Zuwairie, Ibrahim, Nor Hidayati, Abd Aziz, Nor Azlina, Ab. Aziz, Saifudin, Razali, Mohd Saberi, Mohamad

    Published 2016
    “…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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  15. 15

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…Applications and improvements to the HKA algorithm suggest that optimization algorithm based on estimation principle has a huge potential in solving a wide variety of optimization problems. …”
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    Thesis
  16. 16

    Overview of metaheuristic: classification of population and trajectory by Zainul Rashid, Zarina

    Published 2010
    “…Some algorithms can be defined if the developer of the system has problem specific knowledge to the solution. …”
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    Monograph
  17. 17

    Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems by Tan, Joe Yee

    Published 2022
    “…In this case, the effectiveness and reliability of RMS is increase by combining the simulation with the optimization algorithm.…”
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    Thesis
  18. 18

    A discrete simulated kalman filter optimizer for combinatorial optimization problems by Suhazri Amrin, Rahmad

    Published 2022
    “…An example of a numerical algorithm is the simulated Kalman filter (SKF). …”
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    Thesis
  19. 19

    The Hybrid of WOABAT-IFDO Optimization Algorithm and Its Application in Crowd Evacuation Simulation by Hamizan, Sharbini, Roselina, Sallehuddin, Habibollah, Haron

    Published 2023
    “…This paper proposes a new hybrid of nature inspired optimization algorithm (IFDO-WOABAT) based on the latest optimization algorithm namely Improved Fitness Dependent Optimization (IFDO) with Whale-Bat Optimization algorithm (WOABAT). …”
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    Proceeding
  20. 20

    Ant colony optimization for rule induction with simulated annealing for terms selection by Saian, Rizauddin, Ku-Mahamud, Ku Ruhana

    Published 2012
    “…This paper proposes a sequential covering based algorithm that uses an ant colony optimization algorithm to directly extract classification rules from the data set.The proposed algorithm uses a Simulated Annealing algorithm to optimize terms selection, while growing a rule.The proposed algorithm minimizes the problem of a low quality discovered rule by an ant in a colony, where the rule discovered by an ant is not the best quality rule, by optimizing the terms selection in rule construction. …”
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